(Sorry for multiple posting. Seems to be my msg is not distributed in my
previous emails)
Dear R users,
I need to do sampling without replacement (bootstraps). I have two variables
(Xvar, Yvar).
I have a correlation from original data set cor(Xvar, Yvar)=0.6174221. I am
doing 5 sampling,
and in each sampling calculating correlations, saving, sorting and getting
95% cutt off point (0.1351877).
I am getting maximum value as 0.3507219 (much smaller than correlation of my
original data).
I repeated the sampling a couple of time and none of them produced a
correlation
coefficient higher than my original data set. However, if I sort out my Xvar
and Yvar and
obtain correlation it is 0.9657125 which is much higher than correlation for my
original data.
I am doing sampling in another program and getting at least 1% higher
correlation than mine.
Now I am getting confused with sampling(random data) in R. My data and codes
for the scenario above are
in the attached file. I want to understand where I am making a mistake. Any
comment is deeply appreciated.
Kind Regards
Seyit Ali
Xvar<-c(0.1818182,0.5384615,0.5535714,0.4680851,0.4545455,0.4385965,0.5185185,0.4035088,0.4901961,0.3650794,0.462963,0.4,0.56,0.3965517,0.4909091,
0.4716981,0.4310345,0.2,0.1509434,0.2647059,0.173913,0.1914894,0.1914894,0.1489362,0.1363636,0.2244898,0.2325581,0.133,0.1818182,0.1702128,
0.2173913,0.2380952,0.1632653,0.5614035,0.3396226,0.4909091,0.3770492,0.5,0.5185185,0.5,0.467,0.4464286,0.362069,0.4285714,0.4561404,
0.4736842,0.4545455,0.417,0.4181818,0.4590164,0.517,0.5423729,0.483,0.5454545,0.4393939,0.5172414,0.4098361,0.4745763,0.4754098,
0.517,0.5,0.4603175,0.42,0.4038462,0.4897959,0.3148148,0.3673469,0.4,0.458,0.3877551,0.4375,0.4117647,0.4313725,0.533,0.3962264,
0.3548387,0.5272727,0.4137931,0.3928571,0.467,0.4210526,0.4363636,0.4545455,0.4310345,0.4237288,0.4814815,0.4912281,0.433,0.4,0.4285714,
0.4516129,0.5090909,0.4464286,0.4642857,0.417,0.4098361,0.4909091,0.3809524,0.5272727,0.4814815,0.5254237,0.627451,0.5,0.5471698,0.5454545,
0.5925926,0.5769231,0.5818182,0.444,0.4915254,0.4727273,0.4107143,0.4285714,0.4310345,0.4237288,0.4285714,0.440678,0.4237288,0.4807692,
0.4150943,0.4615385,0.4107143,0.4814815,0.4074074,0.4210526,0.5263158,0.440678,0.4576271,0.5344828,0.5,0.5636364,0.4677419,0.5,0.5192308,
0.4642857,0.5090909,0.58,0.4482759,0.5098039,0.4035088,0.4210526,0.5098039,0.4385965,0.5283019,0.5471698,0.625,0.4310345,0.4912281,0.5283019,
0.4576271,0.5471698,0.4745763,0.4821429)
Yvar<-c(0.2553191,0.4107143,0.5660377,0.389,0.3606557,0.2898551,0.3818182,0.4,0.4,0.3278689,0.2903226,0.4074074,0.4181818,0.3,0.2238806,0.3728814,
0.3709677,0.2307692,0.2830189,0.2244898,0.2142857,0.2131148,0.22,0.2258065,0.2321429,0.2,0.2264151,0.22,0.2115385,0.2459016,0.117,0.1785714,
0.2068966,0.6,0.4285714,0.3134328,0.4461538,0.3965517,0.4769231,0.6181818,0.4827586,0.3709677,0.3965517,0.4821429,0.4545455,0.359375,0.4576271,
0.4516129,0.5272727,0.4603175,0.4,0.4912281,0.5384615,0.5,0.4516129,0.4126984,0.4655172,0.5263158,0.4925373,0.358209,0.4285714,0.4920635,
0.4482759,0.3235294,0.4,0.4375,0.440678,0.3898305,0.35,0.4528302,0.58,0.4153846,0.3174603,0.5185185,0.3870968,0.2894737,0.3709677,0.369863,
0.3676471,0.3636364,0.3088235,0.328125,0.4032258,0.4084507,0.3188406,0.3636364,0.3823529,0.2816901,0.472,0.5,0.3521127,0.4393939,0.3787879,
0.453125,0.4324324,0.4057971,0.4545455,0.4492754,0.5,0.4098361,0.4067797,0.367,0.3928571,0.4285714,0.5,0.2923077,0.4561404,0.45,0.5538462,
0.4626866,0.4057971,0.3676471,0.5322581,0.5428571,0.375,0.4411765,0.4571429,0.4,0.3846154,0.3870968,0.4915254,0.530303,0.4375,0.4918033,0.4179104,
0.4032258,0.3606557,0.5178571,0.4848485,0.390625,0.375,0.4375,0.367,0.4,0.4477612,0.2571429,0.4032258,0.3382353,0.4814815,0.4090909,0.3548387,
0.4821429,0.5,0.557377,0.433,0.5454545,0.4590164,0.3943662,0.5076923,0.5,0.3283582,0.3676471,0.559322)
my.cor<-cor(Xvar, Yvar)
print(my.cor)
nperm<-4
Perm.Cor<-NULL
for (iperm in 1:nperm) {
XvarNew<-sample(Xvar, size=length(Xvar), replace=FALSE)
YvarNew<-sample(Yvar, size=length(Yvar), replace=FALSE)
perm.cor<-cor(XvarNew, YvarNew)
Perm.Cor<-c(Perm.Cor, perm.cor)
}
print(max(Perm.Cor))
XvarSorted<-sort(Xvar, decreasing=TRUE)
YvarSorted<-sort(Yvar, decreasing=TRUE)
max.cor<-cor(XvarSorted, YvarSorted)
print(max.cor)
if(mat.cor>0) Perm.Cor.Sorted<-sort(Perm.Cor, decreasing=TRUE)
if(mat.cor<0) Perm.Cor.Sorted<-sort(Perm.Cor, decreasing=FALSE)
T95<-Perm.Cor.Sorted[(nperm+1)*0.05]# 95% treshold value
T99<-Perm.Cor.Sorted[(nperm+1)*0.01]# 99% treshold value
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